Extend business reporting with text analysis.
使用文本分析扩展业务报告。
Perl is an excellent language for text analysis.
Perl是用于文本分析的一种出色语言。
An Annotator is the basic text analysis component.
标注器是基本的文本分析组件。
Overview - OmniFind processing and custom text analysis.
概述——omnifind处理和定制的文本分析。
SKILL_REPORT: The table containing the text analysis results.
SKILL_REPORT：包含文本分析结果的表。
Each annotator implements one specific text analysis function.
每个注释器实现一个特定的文本分析功能。
The basic task behind text analysis is Information Extraction (IE).
文本分析背后的基本任务是信息提取(Information Extraction,IE)。
Select the Factbook_Concepts as the rule file to be used in the text analysis.
选择 Factbook_Concepts作为文本分析中使用的规则文件。
The CPAN Lingua modules can give you power and flexibility in any text analysis task.
CPANLingua模块可以在任何文本分析任务中为您提供功能和灵活性。
For more complex text analysis tasks, the development of a custom annotator may be of interest.
对于更复杂的文本分析任务，可能需要开发定制的注释器。
Many additional text analysis components including word splitting, regex and sounds-like filters.
多个新增的文本分析组件，包括分词、正则表达式过滤器和近似读音过滤器。
This section describes how to create the skills report that displays the results of the text analysis.
本节介绍如何创建显示文本分析结果的技能报告。
Following are two examples of business scenarios that illustrate the value of text analysis technology.
下面两个业务场景示例说明文本分析技术的价值。
The output of text analysis consists of the original text along with additional metadata about the text.
文本分析的输出由原始文本和关于文本的附加元数据组成。
To have the collection use the auto-classifier, it needs to be associated with the new text analysis engine.
为了让集合使用自动分类器，需要将集合与新的文本分析引擎关联起来。
It also described some possibilities regarding how text analysis results can be used to create new insights.
还讨论了通过文本分析发现新信息的一些可能性。
This lets you extend the text analysis capabilities of InfoSphere Warehouse to meet your specific requirements.
这允许您扩展InfoSphereWarehouse的文本分析功能，以满足特定的需求。
Additional text analysis would enable us to find other relations between people, based on statements in the text.
其他文本分析使我们能够根据文本中的语句寻找人们之间的其他关系。
You must specify which are the text fields that you want to run through text analysis (natural language processing).
您必须指定要在哪些文本字段上运行文本分析(自然语言处理)。
This article is the third and last of this three part series about the use of InfoSphere Warehouse for text analysis.
本文是关于使用InfoSphere Warehouse进行文本分析的系列文章的第3部分，也是最后部分。
In one of our projects, there was need for unstructured text analysis; UIMA looked like doing exactly what was needed.
我们曾经有一个项目，它需要非结构化的文本分析；uima似乎是理想之选。
IBM has already announced that several business partners are making UIMA-compatible text analysis components available.
IBM已经声明有几家业务合作伙伴正在开发与uima兼容的文本分析组件。
Some of the most interesting and active fields related to text analysis are scientific research and sentiment detection.
与文本分析相关的最有趣、最活跃的领域是科学研究和情感探测。
The rest of this article briefly presents the basic architecture of InfoSphere Warehouse and its text analysis features.
本文的其余部分简要介绍InfoSphereWarehouse及其文本分析特性的基本体系结构。
You can also use custom Apache UIMA compliant text analysis components to implement more advanced text analysis solutions.
您还可以使用定制的ApacheUIMA文本分析组件实现更高级的文本分析解决方案。
In this section, you will create a Cognos report that displays the text analysis results you extracted in the last section.
在本节中，您将创建一个Cognos报告，显示您从上一小节中提取的文本分析结果。
Although T-SQL is extremely powerful for most data processing, it provides little support for text analysis or manipulation.
尽管T - SQL对多数数据处理而言极其强大，但它对文本分析或操作所提供的支持却很少。
Semantic search requires text analysis components to analyze documents for concepts of relevance and create searchable metadata.
语义搜索要求文本分析组件分析文档的概念相关性并创建可搜索的元数据。
In addition to the common text analysis methods above, InfoSphere Warehouse allows the use of Apache UIMA compatible annotators.
除了上面的常用文本分析方法之外，InfoSphere Warehouse还允许使用与Apacheuima兼容的注解器。
But it is easy to consume the result tables containing the text analysis results, like any other database table in the Cognos report.
但是可以很轻松地使用包含文本分析结果的结果表，就如同使用Cognos报告中的任何其他数据库表一样。
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